• Gu, Bonsang (Department of Economics, Hankuk University of Foreign Studies) ;
  • Song, Joonhyuk (Department of Economics, Hankuk University of Foreign Studies)
  • Received : 2017.09.18
  • Accepted : 2017.10.08
  • Published : 2017.11.30


In this paper, machine learning models employed in various fields are discussed and applied to KOSPI200 stock index return forecasting. The results of hyperparameter analysis of the machine learning models are also reported and practical methods for each model are presented. As a result of the analysis, Support Vector Machine and Artificial Neural Network showed a better performance than k-Nearest Neighbor and Random Forest.


Supported by : Hankuk University


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